Experimental and Numerical Studies of the Effects of Upper Surface Roughness on Aileron Performance
Bibliographic record
Abstract
Wind tunnel studies were carried out to observe the effects of distributed roughness on the upper surface of a NACA 4415 wing-aileron combination. Viscous analysis of the corresponding 2-D airfoil with an aileron was carried out using the 2-D structured multi-block Navier-Stokes (NS) solver NPARC. The two equation k-ω model was used without wall functions as it allows the specification of a surface roughness through the wall boundary condition. Three different configurations, i.e., the Fokker F-28 MK1000 aircraft with aileron deflections, a NASA LS(1)-0417 wing-flap combination and the NACA 4415 wing-aileron combination, were investigated using the 3-D potential/viscous interaction solver PMAL3D. The results of the experiment, 2-D and 3-D numerical calculations were analyzed and compared where suitable. Generally, the numerical studies were consistent with the experiments and showed similar reductions in maximum lift and stall angle of attack. It is also shown from the present work that roughness on an aircraft's lifting surfaces will have significant effects on its aerodynamics and controllability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".